Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Design Example: Calculating Safe Diameter for Wind-Exposed Disc01:17

Design Example: Calculating Safe Diameter for Wind-Exposed Disc

55
Assessing safety in wind-exposed installations is crucial to preventing potential failures. This example explores the calculation and design adjustments needed to mount a circular disc on a building facade, where wind forces are a primary concern. A 4-meter diameter disc was initially designed as an aesthetic feature facing winds at a velocity of 25 meters per second, with an air density of 1.25 kilograms per cubic meter. Given these conditions, the drag force on the disc was determined using...
55
Wind Turbine Machine Models01:24

Wind Turbine Machine Models

122
In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
122
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

408
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
408
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

43
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
43
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

444
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
444
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

120
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
120

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Failure Lifetime Evaluation Based on Accelerated Generalized Wiener Degradation Process Models with Random Diffusion Coefficients.

Entropy (Basel, Switzerland)·2026
Same author

Reliability Modeling Method for Constant Stress Accelerated Degradation Based on the Generalized Wiener Process.

Entropy (Basel, Switzerland)·2025
Same author

Remaining Useful Life (RUL) Prediction Based on the Bivariant Two-Phase Nonlinear Wiener Degradation Process.

Entropy (Basel, Switzerland)·2025
Same author

E-Bayesian and H-Bayesian Inferences for a Simple Step-Stress Model with Competing Failure Model under Progressively Type-II Censoring.

Entropy (Basel, Switzerland)·2023
Same author

Multicomponent Stress-Strength Model Based on Generalized Progressive Hybrid Censoring Scheme: A Statistical Analysis.

Entropy (Basel, Switzerland)·2022
Same author

Survivin, the promising target in hepatocellular carcinoma gene therapy.

Cancer biology & therapy·2008

Related Experiment Video

Updated: Jun 23, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.0K

A Circular-Linear Probabilistic Model Based on Nonparametric Copula with Applications to Directional Wind Energy

Jie Liu1, Zaizai Yan1

  • 1College of Science, Inner Mongolia University of Technology, Hohhot 010051, China.

Entropy (Basel, Switzerland)
|June 26, 2024
PubMed
Summary
This summary is machine-generated.

A new nonparametric copula model accurately estimates wind speed and direction probability, revealing abundant wind resources in Inner Mongolia. This improves wind farm siting and turbine design for optimal energy capture.

Keywords:
copula modelsdirectional wind energy assessmentnonparametric kernel estimationwind directionwind speed

More Related Videos

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.7K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.3K

Related Experiment Videos

Last Updated: Jun 23, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.0K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.7K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.3K

Area of Science:

  • Renewable Energy Systems
  • Statistical Modeling
  • Atmospheric Science

Background:

  • Directional wind energy assessment relies on joint probability density functions of wind speed and direction.
  • Accurate modeling is crucial for optimizing wind farm performance and turbine design.

Purpose of the Study:

  • To propose and investigate a nonparametric joint probability estimation system for wind velocity and direction using copulas.
  • To compare the proposed method with parametric copula models and models ignoring dependency.

Main Methods:

  • Developed a nonparametric copula method using optimal bandwidth algorithms and transformation techniques.
  • Implemented the Kernel Density Estimation-Copula-Cross-Validation (KDE-COP-CV) model.
  • Analyzed joint probability distributions and correlation between wind speed and direction.

Main Results:

  • The nonparametric copula model significantly outperforms other methods in fitting joint probability distributions.
  • The KDE-COP-CV model enables reliable analysis of wind power density fluctuations with wind direction.
  • Inner Mongolia exhibits abundant wind resources, with peak power density linked to direction at maximum speeds.

Conclusions:

  • The nonparametric copula approach is advantageous for directional wind energy assessment.
  • Wind resources in the studied Inner Mongolia regions are concentrated in NW and W directions.
  • Findings support enhanced accuracy in wind farm micro-siting and turbine generator optimization.